INTRO NOTE: Laboratory for Informatics Development was impacted by departure of Dr. Jim Cimino (left NIH in March 2015). We hope that the lab can be re-convened once a new director is found in a national search. Despite this fact, a report is submitted in hope of re-instantiation of the lab. REPORT: This summary is organized the by different aspects of the project. Improve access to data: ======================= Access to research data needs to balance scientific requirements with privacy regulations. We continued our effort to explore regulatory rules for accessing data of deceased patients stored in Electronic Health Record. In 2014, we published additional paper (ref 2) that describes a problem in de-identification of textual clinical reports of deceased patients. Such report may contain secondary protected health information (information about living relatives). Our paper explored how this problem can be dealt with using a tool developed by National Library of Medicine. (NLM Scrubber). Data organization: ======================= We continued to explored the best way to organize and maintain large healthcare Big Data datasets. We have contributed to international efforts within the Observational Health Data Sciences and Informatics (OHDSI) (ref 1) Clinical research enterprise: ======================= Within NIH IRP, we explored how clinical protocols can be represented using a standard format. After evaluation of several options, we picked Clinical Data Interchange Standards Consortium (CDISC) Operational Data Model (ODM) format. We published a formal evaluation using one NIH IRP protocol as a cast study. (ref 3) Clinical Bioinformatics: ======================= BTRIS contains whole exome sequencing data and we continued to explore how this data can be best organized and analyzed together with genomic knowledge bases. We published a perspective paper that outlines the challenges that have to be overcome and recommendations for future development of clinical bioinformatics. (ref 4) Development of clinical decision support (that uses genomic data) is a key future challenge. We continue to explore the domain of decision support in general (ref 5)